Biomass-based stochastic model for the transfer of polychlorinated biphenyls in a marine food web

Abstract

Clarifying the state of marine pollution is important for evaluating the health risk to predators in the marine food web such as fishes and mammals. Although previous studies have generally modeled marine pollution targeting a single organism, this study focused on the transfer of marine pollution in terms of ecological network. In this study, a biomass-based stochastic model was constructed for the transfer of 2,2',4,4',5,5'-hexachlorobiphenyl (PCB153) in a coupled pelagic-benthic system targeting populations of species. Incorporating the populations of species allows for discussions on predation pressure and anthropogenic activities such as fishing. The biomass parameters representing populations of species were set by using published data on the ecosystem in Tokyo Bay, Japan and were represented by probability density distributions to reflect population uncertainty. The PCB153 concentrations computed by the model were then compared with observations for validation. The results showed that the probability density distributions of PCB153 concentrations in marine species had a long tail to the right, which indicated the occurrence probabilities of individual organisms having considerably high contamination levels. A theoretical analysis was performed to quantify the response of species (e.g., fish, plankton, and benthos) to PCB153 accumulation accounting for population uncertainty, which indicated that a reduction in the population of predator species may contribute to the occurrence of high PCB153 concentrations in individual organisms in other species. The obtained probability density distributions were then used to compare the PCB153 human intake through ingesting seafood with the human's acceptable daily intake. The model can quantitatively demonstrate the probability distributions of PCB153 concentrations in marine species and PCB153 intake by humans through seafood, to which more attention should be paid.

Keywords: Bioaccumulation; Coupled pelagic–benthic system; Marine environmental risk assessment; Persistent organic pollutants; Pollutant transfer model; Probabilistic approach.